n.a.
We develop a model of optimal schooling investments and estimate it using new data on approximately 700 identical twins. We estimate an average return to schooling of 9 percent for identical twins, but estimated returns appear to be slightly higher for less able individuals. Simple cross-section estimates are marginally upward biased. These empirical results imply that abler individuals attain more schooling because they face lower marginal costs of schooling, not because of higher marginal benefits.
This paper surveys various econometric issues that arise in estimating a relation between the logarithm of earnings, schooling, and other variables and focuses on the problem of "ability" as a left-out variable and the various solutions to it. It points out that in optimizing models the "ability bias" need not be positive and shows, using recent analyses of NLS data, that when schooling is treated symmetrically, allowing it too to be subject to errors of measurement and correlated to the disturbance in the earnings function, the usual conclusion of a significantly positive "ability bias" in the estimated schooling coefficients.
The chapter considers the economic interpretation of Mincerian earnings functions and how the availability of repeated cross section and panel data improves rate of return estimates. The authors present a general nonparametric approach for estimating marginal internal rates of return that takes into account tuition, income taxes and uncertainty. They find that cohort-based models fitted on repeated cross section data provide more reliable estimates of ex post returns. New panel data methods for estimating the uncertainty and psychic costs facing agents are reviewed. The evidence demonstrates that there are large psychic costs of schooling. This helps to explain why persons do not attend school even though the financial rewards for doing so are high.
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